Complex NeuronalNetworks

Luciano da F. Costa, 12 Nov 2004

“Truth in science can be defined as the working hypothesis best suited to open the way to the next better one.”

Konrad Lorenz

PLAN OF THE PRESENTATION

i. Luciano’s GroupI. ShapeII. FunctionIII. EvolutionIV. Neural SynthesisV. Neural PercolationVI. Complex Network PrimerVII. Complex Neural NetworksVIII.The Future

Image/Shape

Analysis

Pattern

Recognition Modeling

I. SHAPE

II. FUNCTION

III. EVOLUTION

Structure Function

Environment

IV. NEURAL SYNTHESIS

V. NEURAL PERCOLATION

No axon

With axon

VI. COMPLEX NETWORKSPRIMER

Raimundo Maria

Joaquim

Lili

J. PintoFernandes

João

Teresa

lampbattery

Network

VII. COMPLEX NEURALNETWORKS

p = 0.1 p = 0.3

unidirectional

p = 0.1 p = 0.3

bidirectional

VIII. THE FUTURE

Alan AlparAmnon AharonyAndreas SchierwagenAntonio RoqueDania H. BritoDavid SchubertEdson T. M. ManoelDietrich StaufferGer RamakersGiorgio Ascoli Heinz WaessleHerbert JelinekJaap Van PeltJaap Van OyenJoan Adler Julia S. TanakaKoiichi SameshimaLeandro CarrijoLeandro EstroziLuis DiambraMarconi Barbosa

Maria C. OliveiraMarinilce SilvaRegina C. CoelhoRoberto M. Cesar JrRodrigo FreireRosane MinguimThomas ArendtUlrich GartnerVincent Coupez

…

FAPESPCNPqCAPESCCIntPró-Reitorias